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Jin S, Yoon JH, Na DL. Effects of workbook training using editorials and newspaper articles in adults with preclinical stage of dementia. Sci Rep 2024; 14:2302. [PMID: 38280933 PMCID: PMC10821911 DOI: 10.1038/s41598-024-52873-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 01/24/2024] [Indexed: 01/29/2024] Open
Abstract
Early detection and intervention in individuals in the pre-clinical stage of dementia are crucial. This study aimed to examine whether there are significant differences in (1) word retrieval, (2) subjective communication ability, (3) intervention satisfaction through the 'Fill-in-the-blanks in editorial and newspaper articles' training in patients with subjective cognitive decline and mild cognitive impairment corresponding to the pre-clinical stage of dementia. Ninety-nine patients (50 in the intervention group and 49 in the control group) aged 50-84 years were administered pre- and post-test after 6 weeks of intervention (30 sessions). Regarding word retrieval, there were significant intervention effects on confrontation naming, semantic fluency, and phonemic fluency. The majority of participants in the intervention group were highly satisfied with the training. In terms of intervention satisfaction, the majority of the participants in the intervention group showed high satisfaction with all the questions. This result confirmed the improvement of word retrieval ability through mass communication content-based 'Fill-in-the-blanks' training, and ultimately helps to provide a clinical basis for applying this intervention to prevent dementia.
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Affiliation(s)
- Sora Jin
- Department of Speech Pathology and Audiology, Graduate School at Hallym University, Chuncheon, South Korea
| | - Ji Hye Yoon
- Division of Speech Pathology and Audiology, Research Institute of Audiology and Speech Pathology, Hallym University, Chuncheon, South Korea.
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
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2
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Jovalekic A, Roé-Vellvé N, Koglin N, Quintana ML, Nelson A, Diemling M, Lilja J, Gómez-González JP, Doré V, Bourgeat P, Whittington A, Gunn R, Stephens AW, Bullich S. Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods. Eur J Nucl Med Mol Imaging 2023; 50:3276-3289. [PMID: 37300571 PMCID: PMC10542295 DOI: 10.1007/s00259-023-06279-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE Amyloid positron emission tomography (PET) with [18F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification. METHODS This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), AmyloidIQ) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled. RESULTS The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods. CONCLUSION This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Vincent Doré
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Australia
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3
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Faldu KG, Shah JS. Alzheimer's disease: a scoping review of biomarker research and development for effective disease diagnosis. Expert Rev Mol Diagn 2022; 22:681-703. [PMID: 35855631 DOI: 10.1080/14737159.2022.2104639] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Alzheimer's disease (AD) is regarded as the foremost reason for neurodegeneration that prominently affects the geriatric population. Characterized by extracellular accumulation of amyloid-beta (Aβ), intracellular aggregation of hyperphosphorylated tau (p-tau), and neuronal degeneration that causes impairment of memory and cognition. Amyloid/tau/neurodegeneration (ATN) classification is utilized for research purposes and involves amyloid, tau, and neuronal injury staging through MRI, PET scanning, and CSF protein concentration estimations. CSF sampling is invasive, and MRI and PET scanning requires sophisticated radiological facilities which limit its widespread diagnostic use. ATN classification lacks effectiveness in preclinical AD. AREAS COVERED This publication intends to collate and review the existing biomarker profile and the current research and development of a new arsenal of biomarkers for AD pathology from different biological samples, microRNA (miRNA), proteomics, metabolomics, artificial intelligence, and machine learning for AD screening, diagnosis, prognosis, and monitoring of AD treatments. EXPERT OPINION It is an accepted observation that AD-related pathological changes occur over a long period of time before the first symptoms are observed providing ample opportunity for detection of biological alterations in various biological samples that can aid in early diagnosis and modify treatment outcomes.
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Affiliation(s)
- Khushboo Govind Faldu
- Department of Pharmacology, Institute of Pharmacy, Nirma University, Ahmedabad, Gujarat, India
| | - Jigna Samir Shah
- Department of Pharmacology, Institute of Pharmacy, Nirma University, Ahmedabad, Gujarat, India
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Smedinga M, Bunnik EM, Richard E, Schermer MHN. Should Doctors Offer Biomarker Testing to Those Afraid to Develop Alzheimer's Dementia? : Applying the Method of Reflective Equilibrium for a Clinical Dilemma. JOURNAL OF BIOETHICAL INQUIRY 2022; 19:287-297. [PMID: 35306635 DOI: 10.1007/s11673-022-10167-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 07/23/2021] [Indexed: 06/14/2023]
Abstract
An increasing number of people seek medical attention for mild cognitive symptoms at older age, worried that they might develop Alzheimer's disease. Some clinical practice guidelines suggest offering biomarker testing in such cases, using a brain scan or a lumbar puncture, to improve diagnostic certainty about Alzheimer's disease and enable an earlier diagnosis. Critics, on the other hand, point out that there is no effective Alzheimer treatment available and argue that biomarker tests lack clinical validity. The debate on the ethical desirability of biomarker testing is currently polarized; advocates and opponents tend to focus on their own line of arguments. In this paper, we show how the method of reflective equilibrium (RE) can be used to systematically weigh the relevant arguments on both sides of the debate to decide whether to offer Alzheimer biomarker testing. In the tradition of RE, we reflect upon these arguments in light of their coherence with other argumentative elements, including relevant facts (e.g. on the clinical validity of the test), ethical principles, and theories on societal ideals or relevant concepts, such as autonomy. Our stance in the debate therefore rests upon previously set out in-depth arguments and reflects a wide societal perspective.
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Affiliation(s)
- Marthe Smedinga
- Department of Medical Ethics, Philosophy and History of Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Reinier Postlaan 4, 6525 GC, Nijmegen, The Netherlands.
| | - Eline M Bunnik
- Department of Medical Ethics, Philosophy and History of Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Edo Richard
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Reinier Postlaan 4, 6525 GC, Nijmegen, The Netherlands
| | - Maartje H N Schermer
- Department of Medical Ethics, Philosophy and History of Medicine, Erasmus MC, Rotterdam, The Netherlands
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5
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Early-phase 18F-FP-CIT and 18F-flutemetamol PET were significantly correlated. Sci Rep 2021; 11:12297. [PMID: 34112926 PMCID: PMC8192502 DOI: 10.1038/s41598-021-91891-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 06/02/2021] [Indexed: 02/02/2023] Open
Abstract
Little is known about whether early-phase PET images of 18F-FP-CIT match those of amyloid PET. Here, we compared early-phase 18F-FP-CIT and 18F-flutemetamol PET images in patients who underwent both within a 1-month interval. The SUVR on early-phase 18F-FP-CIT PET (median, 0.86) was significantly lower than that of 18F-flutemetamol PET (median, 0.91, p < 0.001) for total brain regions including all cerebral lobes and central structures. This significant difference persisted for each brain region except central structures (p = 0.232). The SUVR of total brain regions obtained from early 18F-FP-CIT PET showed a very strong correlation with that of 18F-flutemetamol PET (rho = 0.80, p < 0.001). Among the kinetic parameters, only R1 showed a statistically significant correlation between the two techniques for all brain regions (rho = 0.89, p < 0.001). R1 from 18F-FP-CIT (median, 0.77) was significantly lower in all areas of the brain compared to R1 from 18F-flutemetamol PET (median, 0.81, p < 0.001).18F-FP-CIT demonstrated lower uptake in cortical brain regions than 18F-flutemetamol on early-phase PET. However, both early-phase PETs demonstrated significant correlation of uptake.
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Dubois B, Villain N, Frisoni GB, Rabinovici GD, Sabbagh M, Cappa S, Bejanin A, Bombois S, Epelbaum S, Teichmann M, Habert MO, Nordberg A, Blennow K, Galasko D, Stern Y, Rowe CC, Salloway S, Schneider LS, Cummings JL, Feldman HH. Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group. Lancet Neurol 2021; 20:484-496. [PMID: 33933186 PMCID: PMC8339877 DOI: 10.1016/s1474-4422(21)00066-1] [Citation(s) in RCA: 381] [Impact Index Per Article: 127.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 01/21/2021] [Accepted: 02/18/2021] [Indexed: 12/13/2022]
Abstract
In 2018, the US National Institute on Aging and the Alzheimer's Association proposed a purely biological definition of Alzheimer's disease that relies on biomarkers. Although the intended use of this framework was for research purposes, it has engendered debate and challenges regarding its use in everyday clinical practice. For instance, cognitively unimpaired individuals can have biomarker evidence of both amyloid β and tau pathology but will often not develop clinical manifestations in their lifetime. Furthermore, a positive Alzheimer's disease pattern of biomarkers can be observed in other brain diseases in which Alzheimer's disease pathology is present as a comorbidity. In this Personal View, the International Working Group presents what we consider to be the current limitations of biomarkers in the diagnosis of Alzheimer's disease and, on the basis of this evidence, we propose recommendations for how biomarkers should and should not be used for diagnosing Alzheimer's disease in a clinical setting. We recommend that Alzheimer's disease diagnosis be restricted to people who have positive biomarkers together with specific Alzheimer's disease phenotypes, whereas biomarker-positive cognitively unimpaired individuals should be considered only at-risk for progression to Alzheimer's disease.
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Affiliation(s)
- Bruno Dubois
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France.
| | - Nicolas Villain
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Memory Clinic, University Hospital of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), Saint John of God Clinical Research Centre, Brescia, Italy
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology and Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Marwan Sabbagh
- Cleveland Clinic, Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Stefano Cappa
- University School for Advanced Studies, Pavia, Italy; RCCS Mondino Foundation, Pavia, Italy
| | - Alexandre Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain; Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain; Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Stéphanie Bombois
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; INSERM, CHU Lille, U1171 - Degenerative and vascular cognitive disorders, University of Lille, Lille, France
| | - Stéphane Epelbaum
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; Inria ARAMIS project team, Inria-APHP collaboratio, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France
| | - Marc Teichmann
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France
| | - Marie-Odile Habert
- AP-HP Department of Nuclear Medicine, Sorbonne University, Paris, France; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institute, Stockholm, Sweden; Theme Aging, The Aging Brain, Karolinska University Hospital, Stockholm, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Douglas Galasko
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, USA
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Stephen Salloway
- Department of Neurology and Department of Psychiatry, Alpert Medical School of Brown University, Providence, RI, USA; Butler Hospital, Providence, RI, USA
| | - Lon S Schneider
- Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Jeffrey L Cummings
- Cleveland Clinic, Lou Ruvo Center for Brain Health, Las Vegas, NV, USA; Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Howard H Feldman
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA; Shiley-Marcos Alzheimer's Disease Research Center, University of California San Diego, La Jolla, CA, USA; Alzheimer Disease Cooperative Study, University of California San Diego, La Jolla, CA, USA
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Nuclear Imaging for the Diagnosis of Cardiac Amyloidosis in 2021. Diagnostics (Basel) 2021; 11:diagnostics11060996. [PMID: 34070853 PMCID: PMC8228334 DOI: 10.3390/diagnostics11060996] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 05/24/2021] [Accepted: 05/27/2021] [Indexed: 01/15/2023] Open
Abstract
Cardiac amyloidosis is caused by the deposition of misfolded protein fibrils into the extracellular space of the heart. The diagnosis of cardiac amyloidosis remains challenging because of the heterogeneous manifestations of the disease. There are many different types of amyloidosis with light-chain (AL) amyloidosis and transthyretin (ATTR) amyloidosis being the most common types of cardiac amyloidosis. Endomyocardial biopsy is considered the gold standard for diagnosing cardiac amyloidosis and differentiating amyloid subtypes, but its use is limited because of the invasive nature of the procedure, with risks for complications and the need for specialized training and centers to perform the procedure. Radionuclide cardiac imaging has recently become the most commonly performed test for the diagnosis of ATTR amyloidosis but is of limited value for the diagnosis of AL amyloidosis. Positron emission tomography has been increasingly used for the diagnosis of cardiac amyloidosis and its applications are expected to expand in the future. Imaging protocols are under refinement to achieve better quantification of the disease burden and prediction of prognosis.
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Ahmed TF, Ahmed A, Imtiaz F. History in perspective: How Alzheimer's Disease came to be where it is? Brain Res 2021; 1758:147342. [PMID: 33548268 DOI: 10.1016/j.brainres.2021.147342] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 01/18/2021] [Accepted: 01/28/2021] [Indexed: 01/03/2023]
Abstract
Treatment of Alzheimer's Disease (AD) remains an unsolved issue despite the pronounced global attention it has received from researchers over the last four decades. Determining the primary cause of the disease is challenging due to its long prodromal phase and multifactorial etiology. Regardless, academic disagreements amongst the scientific community have helped in making significant advancements in underpinning the molecular basis of disease pathogenesis. Substantial development in fluid and imaging biomarkers for AD led to a sharp turn in defining the disease as a molecular construct, dispensing its clinical definition. With conceptual progress, revisions in the diagnostic criteria of AD were made, culminating into the research framework proposed by National Institute on Aging and Alzheimer's Association in 2018 which unified different stages of the disease continuum, giving a common language of AT(N)1 classification to researchers. With realization that dementia is the final stage of AD spectrum, its early diagnosis by means of cerebrospinal fluid biomarkers, Positron Emission Tomography and Magnetic Resonance Imaging of the brain holds crucial importance in discovering ways of halting the disease progression. This article maps the insights into the pathogenesis as well as the diagnostic criteria and tests for AD as these have evolved over time. A contextualized timeline of how the understanding of AD has matured with advancing knowledge allows future research to be directed and unexplored avenues to be prioritized.
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Affiliation(s)
- Tehniat F Ahmed
- Department of Biochemistry, Institute of Biomedical Sciences, Dow University of Health Sciences, Karachi, Pakistan.
| | - Affan Ahmed
- Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan
| | - Fauzia Imtiaz
- Department of Biochemistry, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan
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Bao YW, Chau ACM, Chiu PKC, Shea YF, Kwan JSK, Chan FHW, Mak HKF. Heterogeneity of Amyloid Binding in Cognitively Impaired Patients Consecutively Recruited from a Memory Clinic: Evaluating the Utility of Quantitative 18F-Flutemetamol PET-CT in Discrimination of Mild Cognitive Impairment from Alzheimer's Disease and Other Dementias. J Alzheimers Dis 2021; 79:819-832. [PMID: 33361593 PMCID: PMC7902948 DOI: 10.3233/jad-200890] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND With the more widespread use of 18F-radioligand-based amyloid-β (Aβ) PET-CT imaging, we evaluated Aβ binding and the utility of neocortical 18F-Flutemetamol standardized uptake value ratio (SUVR) as a biomarker. OBJECTIVE 18F-Flutemetamol SUVR was used to differentiate 1) mild cognitive impairment (MCI) from Alzheimer's disease (AD), and 2) MCI from other non-AD dementias (OD). METHODS 109 patients consecutively recruited from a University memory clinic underwent clinical evaluation, neuropsychological test, MRI and 18F-Flutemetamol PET-CT. The diagnosis was made by consensus of a panel consisting of 1 neuroradiologist and 2 geriatricians. The final cohort included 13 subjective cognitive decline (SCD), 22 AD, 39 MCI, and 35 OD. Quantitative analysis of 16 region-of-interests made by Cortex ID software (GE Healthcare). RESULTS The global mean 18F-Flutemetamol SUVR in SCD, MCI, AD, and OD were 0.50 (SD-0.08), 0.53 (SD-0.16), 0.76 (SD-0.10), and 0.56 (SD-0.16), respectively, with SUVR in SCD and MCI and OD being significantly lower than AD. Aβ binding in SCD, MCI, and OD was heterogeneous, being 23%, 38.5%, and 42.9% respectively, as compared to 100% amyloid positivity in AD. Using global SUVR, ROC analysis showed AUC of 0.868 and 0.588 in differentiating MCI from AD and MCI from OD respectively. CONCLUSION 18F-Flutemetamol SUVR differentiated MCI from AD with high efficacy (high negative predictive value), but much lower efficacy from OD. The major benefit of the test was to differentiate cognitively impaired patients (either SCD, MCI, or OD) without AD-related-amyloid-pathology from AD in the clinical setting, which was under-emphasized in the current guidelines proposed by Amyloid Imaging Task Force.
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Affiliation(s)
- Yi-Wen Bao
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Anson C M Chau
- Department of Medical Imaging, The University of Hong Kong (Shenzhen) Teaching Hospital , The University of Hong Kong, Hong Kong SAR, China
| | - Patrick Ka-Chun Chiu
- Division of Geriatrics, Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China
| | - Yat Fung Shea
- Division of Geriatrics, Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China
| | - Joseph S K Kwan
- Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - Felix Hon Wai Chan
- Division of Geriatrics, Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
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Bogolepova A, Vasenina E, Gomzyakova N, Gusev E, Dudchenko N, Emelin A, Zalutskaya N, Isaev R, Kotovskaya Y, Levin O, Litvinenko I, Lobzin V, Martynov M, Mkhitaryan E, Nikolay G, Palchikova E, Tkacheva O, Cherdak M, Chimagomedova A, Yakhno N. Clinical Guidelines for Cognitive Disorders in Elderly and Older Patients. Zh Nevrol Psikhiatr Im S S Korsakova 2021. [DOI: 10.17116/jnevro20211211036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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11
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Raman F, Grandhi S, Murchison CF, Kennedy RE, Landau S, Roberson ED, McConathy J. Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER) Methodology for Research and Clinical Brain PET Applications. J Alzheimers Dis 2020; 70:1241-1257. [PMID: 31322571 DOI: 10.3233/jad-190329] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Tools for efficient evaluation of amyloid- and tau-PET images are needed in both clinical and research settings. OBJECTIVE This study was designed to validate a semi-automated image analysis methodology, called Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER). We tested BLAzER using two different segmentation platforms, FreeSurfer (FS) and Neuroreader (NR), for regional brain PET quantification in participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. METHODS 127 amyloid-PET and 55 tau-PET studies with volumetric MRIs were obtained from ADNI. The BLAzER methodology utilizes segmentation of MR images by FS or NR, then visualizes and quantifies regional brain PET data using FDA-cleared software (MIM), enabling quality control to ensure optimal registration and to detect segmentation errors. RESULTS BLAzER analysis required ∼5 min plus segmentation time. BLAzER using FS segmentation showed strong agreement with ADNI for global amyloid-PET standardized uptake value ratios (SUVRs) (r = 0.9922, p < 0.001) and regional tau-PET SUVRs across all Braak staging regions (r > 0.97, p < 0.001) with high inter-operator reproducibility (ICC > 0.97) and nearly identical dichotomization as amyloid-positive or -negative (2 discrepant cases out of 127). Comparing FS versus NR segmentation with BLAzER, global SUVRs were strongly correlated for amyloid-PET (r = 0.9841, p < 0.001), but were systematically higher (4% on average) with NR, likely due to more inclusion of white matter with NR-defined regions. CONCLUSIONS BLAzER provides an efficient methodology for regional brain PET quantification. FDA-cleared components and visualization of registration reduce barriers between research and clinical applications.
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Affiliation(s)
- Fabio Raman
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA.,Center for Neurodegeneration and Experimental Therapeutics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sameera Grandhi
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Charles F Murchison
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Richard E Kennedy
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA, USA
| | - Erik D Roberson
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA.,Center for Neurodegeneration and Experimental Therapeutics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jonathan McConathy
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA
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McDade E, Bednar MM, Brashear HR, Miller DS, Maruff P, Randolph C, Ismail Z, Carrillo MC, Weber CJ, Bain LJ, Hake AM. The pathway to secondary prevention of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2020; 6:e12069. [PMID: 32885024 PMCID: PMC7453146 DOI: 10.1002/trc2.12069] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 07/09/2020] [Indexed: 11/11/2022]
Abstract
Alzheimer's disease (AD) is a continuum consisting of a preclinical stage that occurs decades before symptoms appear. As researchers make advances in investigating the continuum, the importance of developing drugs for secondary prevention is garnering increased discussion. For efficacious drug development for secondary prevention it is important to define what are the earliest biological stages of AD. The Alzheimer's Association Research Roundtable convened November 27 to 28, 2018 to focus on pre-clinical AD. This review will address the biological approach to defining pre-clinical AD, detection, identification of at-risk individuals, and lessons learned from trials such as A4 and TOMMORROW.
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Affiliation(s)
- Eric McDade
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
| | - Martin M. Bednar
- Takeda Pharmaceuticals International Co.Americas, Inc.CambridgeMassachusettsUSA
| | | | | | | | - Christopher Randolph
- MedAvante‐ProPhaseHamiltonNew JerseyUSA
- Department of NeurologyLoyola University Medical CenterMaywoodIllinoisUSA
| | - Zahinoor Ismail
- Cumming School of MedicineThe University of CalgaryCalgaryCanada
| | | | | | - Lisa J. Bain
- Independent Science WriterElversonPennsylvaniaUSA
| | - Ann Marie Hake
- Eli Lilly and CompanyIndianapolisIndianaUSA
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
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13
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Giovacchini G, Giovannini E, Borsò E, Lazzeri P, Duce V, Ferrando O, Foppiano F, Ciarmiello A. Impact of Tracer Retention Levels on Visual Analysis of Cerebral [ 18F]- Florbetaben Pet Images. Curr Radiopharm 2020; 14:70-77. [PMID: 32727344 DOI: 10.2174/1874471013666200729155717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 06/15/2020] [Accepted: 06/19/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND To compare visual and semi-quantitative analysis of brain [18F]Florbetaben PET images in Mild Cognitive Impairment (MCI) patients and relate this finding to the degree of ß-amyloid burden. METHODS A sample of 71 amnestic MCI patients (age 74 ± 7.3 years, Mini Mental State Examination 24.2 ± 5.3) underwent cerebral [18F]Florbetaben PET/CT. Images were visually scored as positive or negative independently by three certified readers blinded to clinical and neuropsychological assessment. Amyloid positivity was also assessed by semiquantitative approach by means of a previously published threshold (SUVr ≥ 1.3). Fleiss kappa coefficient was used to compare visual analysis (after consensus among readers) and semi-quantitative analysis. Statistical significance was taken at P<0.05. RESULTS After the consensus reading, 43/71 (60.6%) patients were considered positive. Cases that were interpreted as visually positive had higher SUVr than visually negative patients (1.48 ± 0.19 vs 1.11 ± 0.09) (P<0.05). Agreement between visual analysis and semi-quantitative analysis was excellent (k=0.86, P<0.05). Disagreement occurred in 7/71 patients (9.9%) (6 false positives and 1 false negative). Agreement between the two analyses was 90.0% (18/20) for SUVr < 1.1, 83% (24/29) for SUVr between 1.1 and 1.5, and 100% (22/22) for SUVr > 1.5 indicating lowest agreement for the group with intermediate amyloid burden. CONCLUSION Inter-rater agreement of visual analysis of amyloid PET images is high. Agreement between visual analysis and SUVr semi-quantitative analysis decreases in the range of 1.1<SUVr <=1.5, where the clinical scenario is more challenging.
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Affiliation(s)
- Giampiero Giovacchini
- Nuclear Medicine Unit S. Andrea Hospital Via Vittorio Veneto, 197 19124 La Spezia, Italy
| | - Elisabetta Giovannini
- Nuclear Medicine Unit S. Andrea Hospital Via Vittorio Veneto, 197 19124 La Spezia, Italy
| | - Elisa Borsò
- Nuclear Medicine Unit S. Andrea Hospital Via Vittorio Veneto, 197 19124 La Spezia, Italy
| | - Patrizia Lazzeri
- Nuclear Medicine Unit S. Andrea Hospital Via Vittorio Veneto, 197 19124 La Spezia, Italy
| | - Valerio Duce
- Nuclear Medicine Unit S. Andrea Hospital Via Vittorio Veneto, 197 19124 La Spezia, Italy
| | | | | | - Andrea Ciarmiello
- Nuclear Medicine Unit S. Andrea Hospital Via Vittorio Veneto, 197 19124 La Spezia, Italy
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14
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Chen TB, Lai YH, Ke TL, Chen JP, Lee YJ, Lin SY, Lin PC, Wang PN, Cheng IH. Changes in Plasma Amyloid and Tau in a Longitudinal Study of Normal Aging, Mild Cognitive Impairment, and Alzheimer's Disease. Dement Geriatr Cogn Disord 2020; 48:180-195. [PMID: 31991443 DOI: 10.1159/000505435] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 12/15/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Changes in cerebrospinal fluid, neuroimaging, and cognitive functions have been used as diagnostic biomarkers of Alzheimer's disease (AD). This study aimed to investigate the temporal trajectories of plasma biomarkers in subjects with mild cognitive impairment (MCI) and patients with AD relative to healthy controls (HCs). METHODS In this longitudinal study, 82 participants (31 HCs, 33 MCI patients, and 18 AD patients) were enrolled. After 3 years, 7 HCs had transitioned to MCI and 10 subjects with MCI had converted to AD. We analyzed plasma amyloid beta (Aβ) and tau proteins at baseline and annually to correlate with biochemical data and neuropsychological scores. RESULTS Longitudinal data analysis showed an evolution of Aβ-related biomarkers over time within patients, whereas tau-related biomarkers differed primarily across diagnostic classifications. An initial steady increase in Aβ42 in the MCI stage was followed by a decrease just prior to clinical AD onset. Hyperphosphorylated tau protein levels correlated with cognitive decline in the MCI stage, but not in the AD stage. CONCLUSION Plasma Aβ and tau levels change in a dynamic, nonlinear, nonparallel manner over the AD continuum. Changes in plasma Aβ concentration are time-dependent, whereas changes in hyperphosphorylated tau protein levels paralleled the clinical progression of MCI. It remains to be clarified whether diagnostic efficiency can be improved by combining multiple plasma markers or combining plasma markers with other diagnostic biomarkers.
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Affiliation(s)
- Ting-Bin Chen
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.,Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan.,Dementia and Parkinson's Disease Integrated Center, Taichung Veterans General Hospital, Taichung, Taiwan.,Center for Geriatrics and Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Yu-Hua Lai
- Department of Neurology, Cheng-Hsin General Hospital, Taipei, Taiwan
| | - Ting-Ling Ke
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Jun-Peng Chen
- Biostatistics Task Force of Taichung Veterans General Hospital, Taichung, Taiwan
| | - Yi-Jung Lee
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan.,Division of Neurology, Department of Medicine, Taipei City Hospital Renai Branch, Taipei, Taiwan
| | - Szu-Ying Lin
- Taipei Municipal Gan-Dau Hospital, Taipei, Taiwan
| | - Po-Chen Lin
- Division of General Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Pei-Ning Wang
- Division of General Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.,Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan.,Brain Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Irene H Cheng
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan, .,Brain Research Center, National Yang-Ming University, Taipei, Taiwan,
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15
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Marquié M, Valero S, Castilla-Marti M, Martínez J, Rodríguez-Gómez O, Sanabria Á, Tartari JP, Monté-Rubio GC, Sotolongo-Grau O, Alegret M, Pérez-Cordón A, Roberto N, de Rojas I, Moreno-Grau S, Montrreal L, Hernández I, Rosende-Roca M, Mauleón A, Vargas L, Abdelnour C, Gil S, Esteban-De Antonio E, Espinosa A, Ortega G, Lomeña F, Pavia J, Vivas A, Tejero MÁ, Gómez-Chiari M, Simó R, Ciudin A, Hernández C, Orellana A, Benaque A, Ruiz A, Tárraga L, Boada M. Association between retinal thickness and β-amyloid brain accumulation in individuals with subjective cognitive decline: Fundació ACE Healthy Brain Initiative. ALZHEIMERS RESEARCH & THERAPY 2020; 12:37. [PMID: 32234080 PMCID: PMC7110730 DOI: 10.1186/s13195-020-00602-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 03/20/2020] [Indexed: 02/06/2023]
Abstract
Background Optical coherence tomography (OCT) of the retina is a fast and easily accessible tool for the quantification of retinal structural measurements. Multiple studies show that patients with Alzheimer’s disease (AD) exhibit thinning in several retinal layers compared to age-matched controls. Subjective cognitive decline (SCD) has been proposed as a risk factor for progression to AD. There is little data about retinal changes in preclinical AD and their correlation with amyloid-β (Aβ) uptake. Aims We investigated the association of retinal thickness quantified by OCT with Aβ accumulation and conversion to mild cognitive impairment (MCI) over 24 months in individuals with SCD. Methods One hundred twenty-nine individuals with SCD enrolled in Fundació ACE Healthy Brain Initiative underwent comprehensive neuropsychological testing, OCT scan of the retina and florbetaben (FBB) positron emission tomography (PET) at baseline (v0) and after 24 months (v2). We assessed the association of sixteen retinal thickness measurements at baseline with FBB-PET status (+/−) and global standardize uptake value ratio (SUVR) as a continuous measure at v0 and v2 and their predictive value on clinical status change (conversion to mild cognitive impairment (MCI)) at v2. Results Mean age of the sample was 64.72 ± 7.27 years; 62.8% were females. Fifteen participants were classified as FBB-PET+ at baseline and 22 at v2. Every 1 μm of increased thickness in the inner nasal macular region conferred 8% and 6% higher probability of presenting a FBB-PET+ status at v0 (OR = 1.08, 95% CI = 1.02–1.14, p = 0.007) and v2 (OR = 1.06, 95% CI = 1.02–1.11, p = 0.004), respectively. Inner nasal macular thickness also positively correlated with global SUVR (at v0: β = 0.23, p = 0.004; at v2: β = 0.26, p = 0.001). No retinal measurements were associated to conversion to MCI over 24 months. Conclusions Subtle retinal thickness changes in the macular region are already present in SCD and correlate with Aβ uptake.
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Affiliation(s)
- Marta Marquié
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain.
| | - Sergi Valero
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Miguel Castilla-Marti
- Clínica Oftalmológica Dr. Castilla, Barcelona, Spain.,Department of Ophthalmology, Hospital del Mar and Hospital de l'Esperança - Parc de Salut Mar, Barcelona, Spain
| | - Joan Martínez
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Octavio Rodríguez-Gómez
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Ángela Sanabria
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Pablo Tartari
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Gemma C Monté-Rubio
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Oscar Sotolongo-Grau
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Montserrat Alegret
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Alba Pérez-Cordón
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Natalia Roberto
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Itziar de Rojas
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Sonia Moreno-Grau
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Laura Montrreal
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Isabel Hernández
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Maitee Rosende-Roca
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Ana Mauleón
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Liliana Vargas
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Carla Abdelnour
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Silvia Gil
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Ester Esteban-De Antonio
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Ana Espinosa
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Gemma Ortega
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Francisco Lomeña
- Department of Radiology, Hospital Clínic i Provincial de Barcelona, Universitat de Barcelona, Barcelona, Spain
| | - Javier Pavia
- Department of Radiology, Hospital Clínic i Provincial de Barcelona, Universitat de Barcelona, Barcelona, Spain
| | - Assumpta Vivas
- Department of Diagnostic Imaging, Clínica Corachan, Barcelona, Spain
| | | | | | - Rafael Simó
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain.,Institut de Recerca Vall d'Hebron, Universitat Autònoma de Barcelona (VHIR-UAB), Barcelona, Spain
| | - Andreea Ciudin
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain.,Institut de Recerca Vall d'Hebron, Universitat Autònoma de Barcelona (VHIR-UAB), Barcelona, Spain
| | - Cristina Hernández
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain.,Institut de Recerca Vall d'Hebron, Universitat Autònoma de Barcelona (VHIR-UAB), Barcelona, Spain
| | - Adelina Orellana
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Alba Benaque
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain
| | - Agustín Ruiz
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Lluís Tárraga
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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Roqué M, Martínez García L, Solà I, Alonso-Coello P, Bonfill X, Zamora J. Toolkit of methodological resources to conduct systematic reviews. F1000Res 2020; 9:82. [PMID: 33082931 PMCID: PMC7542253 DOI: 10.12688/f1000research.22032.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/30/2020] [Indexed: 09/20/2023] Open
Abstract
Background: Systematic reviews (SR) can be classified by type depending on the research question they are based on. This work identifies and describes the most relevant methodological resources to conduct high-quality reviews that answer clinical questions regarding prevalence, prognosis, diagnostic accuracy and efficacy of interventions. Methods: Methodological resources have been identified from literature searches and consulting guidelines from institutions that develop SRs. The selected resources are organized by type of SR, and stage of development of the review (formulation of the research question, development of the protocol, literature search, risk of bias assessment, synthesis of findings, assessment of the quality of evidence, and report of SR results and conclusions). Results: Although the different types of SRs are developed following the same steps, each SR type requires specific methods, differing in characteristics and complexity. The extent of methodological development varies by type of SR, with more solid guidelines available for diagnostic accuracy and efficacy of interventions SRs. This methodological toolkit describes the most up-to-date risk of bias instruments: Quality in Prognostic Studies (QUIPS) tool and Prediction model study Risk Of Bias Assessment Tool (PROBAST) for prognostic SRs, Quality assessment of diagnostic accuracy studies tool (QUADAS-2) for diagnostic accuracy SRs, Cochrane risk of bias tool (ROB-2) and Risk of bias in non-randomised studies of interventions studies tool (ROBINS-I) for efficacy of interventions SRs, as well as the latest developments on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Conclusions: This structured compilation of the best methodological resources for each type of SR may prove to be a very useful tool for those researchers that wish to develop SRs or conduct methodological research works on SRs.
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Affiliation(s)
- Marta Roqué
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Laura Martínez García
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Ivan Solà
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Pablo Alonso-Coello
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Xavier Bonfill
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Autonomous University of Barcelona, Bellaterra, Spain
| | - Javier Zamora
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Clinical Biostatistics Unit, Ramón y Cajal Health Research Institute, Madrid, Spain
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17
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Roqué M, Martínez García L, Solà I, Alonso-Coello P, Bonfill X, Zamora J. Toolkit of methodological resources to conduct systematic reviews. F1000Res 2020; 9:82. [PMID: 33082931 PMCID: PMC7542253 DOI: 10.12688/f1000research.22032.3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/12/2020] [Indexed: 12/21/2022] Open
Abstract
Background: Systematic reviews (SR) can be classified by type depending on the research question they are based on. This work identifies and describes the most relevant methodological resources to conduct high-quality reviews that answer health care questions regarding prevalence, prognosis, diagnostic accuracy and effects of interventions. Methods: Methodological resources have been identified from literature searches and consulting guidelines from institutions that develop SRs. The selected resources are organized by type of SR, and stage of development of the review (formulation of the research question, development of the protocol, literature search, risk of bias assessment, synthesis of findings, assessment of the quality of evidence, and report of SR results and conclusions). Results: Although the different types of SRs are developed following the same steps, each SR type requires specific methods, differing in characteristics and complexity. The extent of methodological development varies by type of SR, with more solid guidelines available for diagnostic accuracy and effects of interventions SRs. This methodological toolkit describes the most up-to-date risk of bias instruments: Quality in Prognostic Studies (QUIPS) tool and Prediction model study Risk Of Bias Assessment Tool (PROBAST) for prognostic SRs, Quality assessment of diagnostic accuracy studies tool (QUADAS-2) for diagnostic accuracy SRs, Cochrane risk of bias tool (ROB-2) and Risk of bias in non-randomised studies of interventions studies tool (ROBINS-I) for effects of interventions SRs, as well as the latest developments on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Conclusions: This structured compilation of the best methodological resources for each type of SR may prove to be a very useful tool for those researchers that wish to develop SRs or conduct methodological research works on SRs.
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Affiliation(s)
- Marta Roqué
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Laura Martínez García
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Ivan Solà
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Pablo Alonso-Coello
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Xavier Bonfill
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Autonomous University of Barcelona, Bellaterra, Spain
| | - Javier Zamora
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Clinical Biostatistics Unit, Ramón y Cajal Health Research Institute, Madrid, Spain
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18
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Roqué M, Martínez García L, Solà I, Alonso-Coello P, Bonfill X, Zamora J. Toolkit of methodological resources to conduct systematic reviews. F1000Res 2020; 9:82. [PMID: 33082931 PMCID: PMC7542253 DOI: 10.12688/f1000research.22032.2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/22/2020] [Indexed: 08/11/2023] Open
Abstract
Background: Systematic reviews (SR) can be classified by type depending on the research question they are based on. This work identifies and describes the most relevant methodological resources to conduct high-quality reviews that answer health care questions regarding prevalence, prognosis, diagnostic accuracy and effects of interventions. Methods: Methodological resources have been identified from literature searches and consulting guidelines from institutions that develop SRs. The selected resources are organized by type of SR, and stage of development of the review (formulation of the research question, development of the protocol, literature search, risk of bias assessment, synthesis of findings, assessment of the quality of evidence, and report of SR results and conclusions). Results: Although the different types of SRs are developed following the same steps, each SR type requires specific methods, differing in characteristics and complexity. The extent of methodological development varies by type of SR, with more solid guidelines available for diagnostic accuracy and effects of interventions SRs. This methodological toolkit describes the most up-to-date risk of bias instruments: Quality in Prognostic Studies (QUIPS) tool and Prediction model study Risk Of Bias Assessment Tool (PROBAST) for prognostic SRs, Quality assessment of diagnostic accuracy studies tool (QUADAS-2) for diagnostic accuracy SRs, Cochrane risk of bias tool (ROB-2) and Risk of bias in non-randomised studies of interventions studies tool (ROBINS-I) for effects of interventions SRs, as well as the latest developments on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Conclusions: This structured compilation of the best methodological resources for each type of SR may prove to be a very useful tool for those researchers that wish to develop SRs or conduct methodological research works on SRs.
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Affiliation(s)
- Marta Roqué
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Laura Martínez García
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Ivan Solà
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Pablo Alonso-Coello
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Xavier Bonfill
- Iberoamerican Cochrane Centre - Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Autonomous University of Barcelona, Bellaterra, Spain
| | - Javier Zamora
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Clinical Biostatistics Unit, Ramón y Cajal Health Research Institute, Madrid, Spain
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de Wilde A, van Buchem MM, Otten RHJ, Bouwman F, Stephens A, Barkhof F, Scheltens P, van der Flier WM. Disclosure of amyloid positron emission tomography results to individuals without dementia: a systematic review. ALZHEIMERS RESEARCH & THERAPY 2018; 10:72. [PMID: 30055660 PMCID: PMC6064628 DOI: 10.1186/s13195-018-0398-3] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Background Disclosure of amyloid positron emission tomography (PET) results to individuals without dementia has become standard practice in secondary prevention trials and also increasingly occurs in clinical practice. However, this is controversial given the current lack of understanding of the predictive value of a PET result at the individual level and absence of disease-modifying treatments. In this study, we systematically reviewed the literature on the disclosure of amyloid PET in cognitively normal (CN) individuals and patients with mild cognitive impairment (MCI) in both research and clinical settings. Methods We performed a systematic literature search of four scientific databases. Two independent reviewers screened the identified records and selected relevant articles. Included articles presented either empirical data or theoretical data (i.e. arguments in favor or against amyloid status disclosure). Results from the theoretical data were aggregated and presented per theme. Results Of the seventeen included studies, eleven reported empirical data and six provided theoretical arguments. There was a large variation in the design of the empirical studies, which were almost exclusively in the context of cognitively normal trial participants, comprising only two prospective cohort studies quantitatively assessing the psychological impact of PET result disclosure which showed a low risk of psychological harm after disclosure. Four studies showed that both professionals and cognitively normal individuals support amyloid PET result disclosure and underlined the need for clear disclosure protocols. From the articles presenting theoretical data, we identified 51 ‘pro’ and ‘contra’ arguments. Theoretical arguments in favor or against disclosure were quite consistent across population groups and settings. Arguments against disclosure focused on the principle of non-maleficence, whereas its psychological impact and predictive value is unknown. Important arguments in favor of amyloid disclosure are the patients right to know (patient autonomy) and that it enables early future decision making. Discussion Before amyloid PET result disclosure in individuals without dementia in a research or clinical setting is ready for widespread application, more research is needed about its psychological impact, and its predictive value at an individual level. Finally, communication materials and strategies to support disclosure of amyloid PET results should be further developed and prospectively evaluated. Electronic supplementary material The online version of this article (10.1186/s13195-018-0398-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Arno de Wilde
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands.
| | - Marieke M van Buchem
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - René H J Otten
- Medical Library, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Femke Bouwman
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.,Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Philip Scheltens
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, the Netherlands
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